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Rigging Fast Deformation Estimation with Neural Computation in Maya

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    Description

    This course aims to educate participants on the innovative integration of machine learning (ML) techniques for deformation approximation within Maya software. Using approximations for (part of) a deformation stack can highly improve interactivity when using complex rigs, and can significantly improve the portability between different applications. It is designed for animators, game developers, VFX artists, and any professional interested in exploring the intersection of ML and 3D animation. This course will explore a demo of a rig with computationally expensive muscle deformations that is reduced to a simple, general, black-box neural network that only requires inputs from the motion system. We'll show the entire setup process in detail. In addition, we'll go over best practices, tips, and limitations to help users get the most out of this tool for their production needs.

    Key Learnings

    • Learn about building a rig with an ML Deformer to achieve interactive speeds.
    • Explore use cases and learn about fine-tuning parameters for optimal use of machine learning.
    • Learn how to integrate ML deformers into a production pipeline (rig, generate, train, and deform).